Open AccessProceedings Article
An Answer Set Programming Environment for High-Level Specification and Visualization of FCA.
Lucas Bourneuf
- 13 Jul 2018
pp 1-12
TL;DR: Biseau is introduced, a programming environment dedicated to the exploration of relations through a graphical display that provides an Answer Set Programming to (graphviz) dot compiler and uses the graphviz software to render in real-time the calculated graphs to user.
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Abstract: This paper introduces Biseau, a programming environment
dedicated to the exploration of relations through a graphical display. The
use of Answer Set Programming enables the production of small code
modules which are easy to maintain and debug since they are very close
to the specifications. This paper shows how a mathematical framework
such as Formal Concept Analysis can be efficiently described at the level
of its properties, without needing a costly development process. We hope
that it will help to quickly adapt a given code to the peculiarities of a data
set, thereby speeding up the development of prototypes. Besides, it will
also help the integration of the ideas of the FCA community in a readable
and shareable format. From a practical point of view, Biseau provides
an Answer Set Programming to (graphviz) dot compiler and uses the
graphviz software to render in real-time the calculated graphs to user,
for instance to produce concept lattices or aoc posets visualizations. Its
relation with existing tools like LatViz and FCAbundles is also discussed.
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Citations
•Proceedings Article
Biseau: An Answer Set Programming Environment for High-Level Specification and Graph Visualization applied to FCA
Lucas Bourneuf
- 25 Jun 2019
TL;DR: Biseau is presented, a programming environment aiming at simplifying the visualization task that takes advantage of Answer Set Programming, enabling user to write, maintain, debug and reuse close to specification encodings, and eventually obtain a graphical display of mathematical relations.
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- 13 Jul 2008
TL;DR: Answer set programming (ASP) is a form of declarative programming oriented towards difficult search problems, particularly useful in knowledge-intensive applications.